- SeqGraphR. API change, emailed them.
- FCMapper. Cannot fix, they need to update their package. I emailed them already.
- PBC I have no idea what's wrong here, wrote them an email.
- SDDE. No idea what's wrong, cannot fix. Emailed them.
- SSN. Cannot fix, their example relies on fine details. Wrote them an email.
- causaleffect. They have a bug, I emailed them. They import packages that export the same names. I emailed them.
- netassoc. Negative loop for KK, emailed them.
- fanovaGraph Relies on cliques returning numeric vectors, emailed them. https://github.com/cran/fanovaGraph/blob/master/tests/testthat/test_fullexample.R#L78
- intergraph Has some saved igraph objects that they need to update, emailed them.
- modMax Need to convert vs to numeric, emailed them. https://github.com/cran/modMax/blob/003ebaa010b8d130a5914dc2bc6cb3eab9496930/R/generalFunctions.R#L229
- nat They need to update test cases, emailed them. https://github.com/cran/nat/blob/master/tests/testthat/test-neuroml-io.R#L37 https://github.com/cran/nat/blob/master/tests/testthat/test-ngraph.R#L63-L65
- outbreaker They have a bug, emailed them. https://github.com/cran/outbreaker/blob/a2dee31ebebba37e1a48c3de90570e198f2e9b7c/R/plot.R#L171
- pcalg They have a bug, is.nan should be is.na here: https://github.com/cran/pcalg/blob/5ebec0ca94df959929a250513a81e73a14c68c76/R/pcalg.R#L7403
- ppiPre They need to update, emailed them. Need lapply(..., as.vector) here: https://github.com/cran/ppiPre/blob/1154c7cc92a778f9d054ccb43c3b2a7a11b5e8e1/R/TopologicSims.r#L316
- treemap They have a bug, I emailed them. https://github.com/cran/treemap/blob/cfa1f28fd3c6bda6fc3a8f1c8208170833f4f131/R/treegraph.R#L98
- FedData They import packages that export the same names. I emailed them.
- clickstream. They import packages that export the same names. I emailed them.
- gromovlab They import packages that export the same names. I emailed them.
- netweavers They import packages that export the same names. I emailed them.
- arulesViz Emailed about conflicting imports. Fixed Error.
- causaleffect. They import packages that export the same names. I emailed them.
-
Compilation warnings. Fixed.
-
BoolNet. Fixed.
-
CePa. Fixed.
-
FCMapper. Cannot fix, they need to update their package. I emailed them already.
-
FedData They import packages that export the same names. I emailed them.
-
FisHiCal. Fixed.
-
FrF2. Fixed.
-
PBC I have no idea what's wrong here, wrote them an email.
-
PROFANCY. Fixed.
-
QuACN. Fixed.
-
RCA. Fixed.
-
ReliabilityTheory. Fixed.
-
SDDE. No idea what's wrong, cannot fix. Emailed them.
-
SINGLE They import packages that export the same names. I emailed them.
-
SOMbrero. Fixed.
-
SSN. Cannot fix, their example relies on fine details. Wrote them an email.
-
SeqGrapheR Does not seem to be my problem.
-
SubpathwayGMir
-
TDA They import packages that export the same names. I emailed them.
-
VineCopula Fixed
-
adegenet The crash happens with the current igraph as well, the same way
-
arulesViz Emailed about conflicting imports. Fixed Error.
-
causaleffect. They have a bug, I emailed them. They import packages that export the same names. I emailed them.
-
cccd Fixed
-
clickstream. They import packages that export the same names. I emailed them.
-
dnet. Fixed
-
fanovaGraph
-
fuzzyMM They import packages that export the same names. I emailed them.
-
gRapfa Fixed
-
gemtc Fixed
-
gromovlab They import packages that export the same names. I emailed them.
-
intergraph Has some saved igraph objects that they need to update, emailed them.
-
loe They import packages that export the same names. I emailed them.
-
modMax
-
nat They need to update test cases, emailed them.
-
netassoc. Negative loop for KK, emailed them.
-
netgen They import packages that export the same names. I emailed them.
-
netweavers They import packages that export the same names. I emailed them.
-
optrees Fixed
-
outbreaker They have a bug, emailed them.
-
pcalg
-
popgraph Fixed.
-
poplite Fixed
-
ppiPre
-
qdap Fixed
-
restlos They import packages that export the same names. I emailed them.
-
secrlinear Fixed
-
structSSI The phyloseq issue does not seem to be my problem. The other one fixed.
-
timeordered Fixed.
-
treemap They have a bug, I emailed them.
Package: FisHiCal Check: examples New result: ERROR Running examples in =E2=80=98FisHiCal-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
data(spatialInc) plotInc(1, spatialInc) # no plot since no spatial incosistency was = detected plotInc(167, spatialInc) =
Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly...
Traceback: 1: base::.Call("R_igraph_mybracket", graph, 10L, PACKAGE =3D "igraph")=
2: get_vs_ref(graph) 3: update_vs_ref(graph) 4: V(g) 5: inherits(v, "igraph.vs") 6: as.igraph.vs(graph, index) 7: get.vertex.attribute(g, "membership", index =3D V(g)) 8: plotInc(167, spatialInc) aborting ... Segmentation fault
Package: PBC Check: examples New result: ERROR Running examples in =E2=80=98PBC-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
xf
t
t
s
=
=
showClass("PBC") Class "PBC" [package "PBC"] =
Name: root graph f dxf dxdyf gra= f Class: character igraph expression expression expression expressio= n =
Name: gradxf gradxdyf BINMAT model density gradien= t Class: expression expression matrix character numeric vecto= r =
Name: nIteration Class: numeric
g <- graph.formula(X1-X3,X2-X3,X3-X4,X4-X5,simplify =3D FALSE) pbcObj <- pbc(g, model=3D"gumbel") Error in matrix(res, ncol =3D 2, byrow =3D TRUE) : =
unimplemented type 'expression' in 'copyMatrix'Calls: pbc ... as.igraph.es -> inherits -> na.omit -> E -> ends -> matr= ix Execution halted
Package: PBC Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... Loading required package: igraph
decompose, spectrum=
union=
=
Error: processing vignette =E2=80=98PBC.Rnw=E2=80=99 failed with diagno= stics: chunk 3 =
Error in matrix(res, ncol =3D 2, byrow =3D TRUE) : =
unimplemented type =E2=80=98expression=E2=80=99 in =E2=80=98copyMatri=Execution halted
Package: PBC Check: running R code from vignettes New result: ERROR Errors in running code in vignettes: when running code in =E2=80=98PBC.Rnw=E2=80=99 ...
=
g <- graph.formula(X1 - X2, X2 - X3, X3 - X4, X4 - =
X5, simplify =3D FALSE)=
myPBC <- pbcGumbel(g) =
When sourcing =E2=80=98PBC.R=E2=80=99:Error: unimplemented type =E2=80=98expression=E2=80=99 in =E2=80=98copy= Matrix=E2=80=99 Execution halted
Package: PBC Check: tests New result: ERROR Running the tests in =E2=80=98tests/optim.R=E2=80=99 failed. Last 13 lines of output: > ## Parameters ## > ################ > theta <- runif(4) > g <- graph.formula(X1-X4,X4-X2,X2-X3,X4-X5,simplify =3D FALSE) > =
> ########################## > ## PBC objects Creation ## > ########################## > myPBCGumbel <- pbcGumbel(g) Error in matrix(res, ncol =3D 2, byrow =3D TRUE) : = unimplemented type 'expression' in 'copyMatrix' Calls: pbcGumbel ... as.igraph.es -> inherits -> na.omit -> E -> ends=-> matrix Execution halted
Package: PROFANCY Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... Loading required package: Matrix Loading required package: lattice Loading required package: igraph
decompose, spectrum=
union=
Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly...
Error: processing vignette =E2=80=98PROFANCY.Rnw=E2=80=99 failed with d= iagnostics: chunk 3 =
Error in assign("me", graph, envir =3D env) : =
use of NULL environment is defunctExecution halted
Package: PROFANCY Check: running R code from vignettes New result: ERROR Errors in running code in vignettes: when running code in =E2=80=98PROFANCY.Rnw=E2=80=99 ... 10: source(output, echo =3D TRUE) 11: doTryCatch(return(expr), name, parentenv, handler) 12: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 13: tryCatchList(expr, classes, parentenv, handlers) 14: tryCatch({ source(output, echo =3D TRUE)}, error =3D function(e)= { cat("\n When sourcing ", sQuote(output), ":\n", sep =3D "") sto= p(conditionMessage(e), call. =3D FALSE, domain =3D NA)}) 15: tools:::.run_one_vignette("PROFANCY.Rnw", "/home/hornik/tmp/CRAN/PR= OFANCY.Rcheck/00_pkg_src/PROFANCY/vignettes", pkgdir =3D "/home/horni= k/tmp/CRAN/PROFANCY.Rcheck/00_pkg_src/PROFANCY") aborting ... Segmentation fault
... incomplete output. Crash?
Package: QuACN Check: examples New result: ERROR Running examples in =E2=80=98QuACN-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
minBalabanID(g) Error in eval(expr, envir, enclos) : object 'X' not found Calls: minBalabanID ... [[.igraph.vs -> [ -> [.igraph.vs -> lazy_eval -= eval -> eval Execution halted
Package: QuACN Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ...
%*%, apply, crossprod, matrix, tcrossprod=
=
dbinom, dnorm, dpois, pnorm=
cbind, pmax, pmin, rbind=
Warning in names(fvi) <- nodes(g) : class =E2=80=98mpfr=E2=80=99 has no =E2=80=98names=E2=80=99 slot; ass= igning a names attribute will create an invalid object
Error: processing vignette =E2=80=98QuACN.Rnw=E2=80=99 failed with diag= nostics: chunk 83 =
Error in eval(expr, envir, enclos) : object =E2=80=98X=E2=80=99 not fou= nd Execution halted
Package: QuACN Check: running R code from vignettes New result: ERROR Errors in running code in vignettes: when running code in =E2=80=98QuACN.Rnw=E2=80=99 ... [1] 17.53585
connectivityID(g, deg =3D vec.degree) [1] 17.53585 =
minConnectivityID(g) =
When sourcing =E2=80=98QuACN.R=E2=80=99:Error: object =E2=80=98X=E2=80=99 not found Execution halted
Package: RCA Check: whether package can be installed Old result: WARNING Found the following significant warnings: glpenv01.c:130:48: warning: incompatible integer to pointer conversio= n returning 'int' from a function with result type 'ENV *' (aka 'struct E= NV *') [-Wint-conversion] glpenv01.c:138:43: warning: incompatible integer to pointer conversio= n returning 'int' from a function with result type 'ENV *' (aka 'struct E= NV *') [-Wint-conversion] See =E2=80=98/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/RCA.Rchec= k/00install.out=E2=80=99 for details. New result: WARNING Found the following significant warnings: glpenv01.c:130:48: warning: incompatible integer to pointer conversio= n returning 'int' from a function with result type 'ENV *' (aka 'struct E= NV *') [-Wint-conversion] glpenv01.c:138:43: warning: incompatible integer to pointer conversio= n returning 'int' from a function with result type 'ENV *' (aka 'struct E= NV *') [-Wint-conversion] See =E2=80=98/home/hornik/tmp/CRAN/RCA.Rcheck/00install.out=E2=80=99 fo= r details.
Package: ReliabilityTheory Check: examples New result: ERROR Running examples in =E2=80=98ReliabilityTheory-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
stem with
data(sccsO5) G <- systemGraphToGenerator(sccsO5[[18]]$graph, 1, 365) Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly... =
Traceback: 1: base::.Call("R_igraph_mybracket", graph, 10L, PACKAGE =3D "igraph")=
2: get_vs_ref(graph) 3: update_vs_ref(graph) 4: V(g) 5: systemGraphToGenerator(sccsO5[[18]]$graph, 1, 365) aborting ... Segmentation fault
Package: SDDE Check: examples New result: ERROR Running examples in =E2=80=98SDDE-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
ted as
=
=
ented nodes)
data(Sample_1) result <- complete_network(g1, g2) Error in assign("me", graph, envir =3D env) : invalid 'envir' argument Calls: complete_network -> V -> update_vs_ref -> assign Execution halted
Package: SOMbrero Check: examples New result: ERROR Running examples in =E2=80=98SOMbrero-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
data(lesmis) set.seed(7383) mis.som <- trainSOM(x.data=3Ddissim.lesmis, type=3D"relational", nb.s= ave=3D10) proj.lesmis <- projectIGraph(mis.som, lesmis) Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly... =
Traceback: 1: base::.Call("R_igraph_mybracket", graph, 10L, PACKAGE =3D "igraph")=
2: get_vs_ref(graph) 3: update_vs_ref(graph) 4: V(the.graph) 5: projectGraph(init.graph, object$clustering, object$parameters$the.g= rid$coord) 6: projectIGraph.somRes(mis.som, lesmis) 7: projectIGraph(mis.som, lesmis) aborting ... Segmentation fault
Package: SOMbrero Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... 9: knit_print.default(x, options =3D options) 10: fun(x, options =3D options) 11: value_fun(ev$value, ev$visible) 12: withVisible(value_fun(ev$value, ev$visible)) 13: withCallingHandlers(withVisible(value_fun(ev$value, ev$visible)), = warning =3D wHandler, error =3D eHandler, message =3D mHandler) 14: handle(pv <- withCallingHandlers(withVisible(value_fun(ev$value, = ev$visible)), warning =3D wHandler, error =3D eHandler, message =3D mHa= ndler)) 15: evaluate_call(expr, parsed$src[[i]], envir =3D envir, enclos =3D en= clos, debug =3D debug, last =3D i =3D=3D length(out), use_try =3D sto= p_on_error !=3D 2L, keep_warning =3D keep_warning, keep_message =3D= keep_message, output_handler =3D output_handler) 16: evaluate::evaluate(code, envir =3D env, new_device =3D FALSE, keep_= warning =3D !isFALSE(options$warning), keep_message =3D !isFALSE(opti= ons$message), stop_on_error =3D if (options$error && options$incl= ude) 0L else 2L, output_handler =3D knit_handlers(options$render, = options)) 17: in_dir(opts_knit$get("root.dir") %n% input_dir(), evaluate::evaluat= e(code, envir =3D env, new_device =3D FALSE, keep_warning =3D !isFALS= E(options$warning), keep_message =3D !isFALSE(options$message), stop_= on_error =3D if (options$error && options$include) 0L else 2L, ou= tput_handler =3D knit_handlers(options$render, options))) 18: block_exec(params) 19: call_block(x) 20: process_group.block(group) 21: process_group(group) 22: withCallingHandlers(if (tangle) process_tangle(group) else process_= group(group), error =3D function(e) { setwd(wd) cat(res= , sep =3D "\n", file =3D output %n% "") message("Quitting from lin= es ", paste(current_lines(i), collapse =3D "-"), " (", knit_c= oncord$get("infile"), ") ") }) 23: process_file(text, output) 24: knit(input, text =3D text, envir =3D envir, encoding =3D encoding, = quiet =3D quiet) 25: (if (grepl("\.[Rr]md$", file)) knit2html else if (grepl("\.[Rr]rs= t$", file)) knit2pdf else knit)(file, encoding =3D encoding, quiet =3D= quiet, envir =3D globalenv()) 26: engine$weave(file, quiet =3D quiet, encoding =3D enc) 27: doTryCatch(return(expr), name, parentenv, handler) 28: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 29: tryCatchList(expr, classes, parentenv, handlers) 30: tryCatch({ engine$weave(file, quiet =3D quiet, encoding =3D enc)= setwd(startdir) find_vignette_product(name, by =3D "weave", engine= =3D engine)}, error =3D function(e) { stop(gettextf("processing vigne= tte '%s' failed with diagnostics:\n%s", file, conditionMessage(e)= ), domain =3D NA, call. =3D FALSE)}) 31: buildVignettes(dir =3D "/home/hornik/tmp/CRAN/SOMbrero.Rcheck/vign_= test/SOMbrero") aborting ... Segmentation fault
Package: SSN Check: examples New result: ERROR Running examples in =E2=80=98SSN-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
#######################################
library(SSN) set.seed(101)
raw1.ssn <- createSSN(n =3D c(10,10),
obsDesign =3D binomialDesign(c(50,50)), predDesign =3D binomialDe=sign(c(100,100)),
- importToR =3D TRUE, path =3D paste(tempdir(),"/sim1", sep =3D ""))
names(raw1.ssn) $Obs [1] "locID" "upDist" "pid" "netID" "rid" =
[6] "ratio" "shreve" "addfunccol" "NEAR_X" "NEAR_Y" =
=
$preds [1] "locID" "upDist" "pid" "netID" "rid" =
[6] "ratio" "shreve" "addfunccol" "NEAR_X" "NEAR_Y" =
=
=
sim1.out <- SimulateOnSSN(raw1.ssn,
- ObsSimDF =3D raw1DFobs,
- PredSimDF =3D raw1DFpred,
- PredID =3D "preds",
- formula =3D ~ X1 + F1,
- coefficients =3D c(1, .5, -1, 1),
- CorModels =3D c("Exponential.tailup", "Exponential.taildown"),
- use.nugget =3D TRUE,
- use.anisotropy =3D FALSE,
- CorParms =3D c(2, 5, 2, 5, 0.1),
- addfunccol =3D "addfunccol")
=
values
sim1DFobs <- getSSNdata.frame(sim1.ssn, "Obs") sim1DFobs[,"Sim_Values"] [1] -1.22221603 4.63912013 2.61728318 2.08787430 2.79048827 1.64= 033148 [7] 3.49540946 1.99945533 5.72195878 1.20537606 2.99037210 1.67= 877369 [13] -0.51200212 1.35291928 3.99476133 0.70740751 1.01256425 5.38= 907795 [19] 2.76542504 3.36835225 1.51621684 1.96676706 1.81892768 -0.80= 520080 [25] 0.05693503 0.69611890 0.07005844 2.86270046 1.93813656 1.66= 973468 [31] 3.95391369 1.16850219 0.36026058 -1.10791594 0.12566414 -1.43= 834661 [37] 0.69236606 2.59446507 1.69784809 3.52564693 1.06980961 -0.30= 536485 [43] -0.09252584 1.58185562 1.97110922 2.39896065 2.70699895 2.89= 575511 [49] 2.82499131 2.98420754 -0.22938636 1.20469100 1.94339172 1.50= 021304 [55] 2.30724767 1.63846283 0.65354338 -0.36399753 2.19599708 -0.55= 693252 [61] -2.45291734 3.19421460 -2.26737820 0.99835279 0.37491736 -0.88= 000103 [67] 1.34138560 3.01037830 0.96254576 0.23918404 3.32474447 2.23= 326315 [73] 1.87103880 2.48801876 0.23901987 -1.20189523 1.45746703 -1.45= 504862 [79] -2.47756017 0.81722022 0.98496416 -2.40688920 1.09409146 -1.14= 140862 [85] 2.80984996 -0.15283142 2.76631989 -1.49042589 2.55362768 -1.07= 074101 [91] 0.53528971 2.61915527 -2.89275396 0.09577112 0.46590269 1.39= 517740 [97] 1.42268596 0.59728284 -2.95525195 4.57564676 sim1DFpred <- getSSNdata.frame(sim1.ssn, "preds") sim1DFpred[,"Sim_Values"] [1] 0.90022179 -0.41282611 4.04054785 3.29128707 3.33055418 2.84= 417972 [7] -2.78260315 2.07483716 3.17869484 -0.60004571 2.90952775 -0.64= 288100 [13] -0.03491546 4.67513772 4.76810022 3.68529578 1.13991597 1.70= 658724 [19] 1.12762684 1.41887483 0.45311675 0.88622539 5.46857129 1.32= 914323 [25] 0.64484278 3.34303984 0.15421007 2.18519934 1.36442289 4.87= 824147 [31] 1.65248755 2.43422956 0.71373275 1.94060359 1.92271221 3.53= 886042 [37] 3.16735849 1.68087713 1.91498299 0.42178747 0.57373418 2.73= 271917 [43] -0.32626370 0.77176114 1.01788214 2.41854045 6.32744102 1.37= 179285 [49] -0.70787537 -1.40514483 0.63303383 -0.48877376 -0.52145761 3.05= 408689 [55] -0.28282582 2.71714904 3.86713443 4.76398834 0.21383758 2.16= 347844 [61] 4.25314770 3.84701713 3.50128009 3.77780398 0.43647427 1.31= 199011 [67] -1.22953430 2.74217901 0.26494851 2.49376613 0.91615371 2.35= 073005 [73] 1.77085946 0.46187341 1.37541422 0.08820810 4.51074452 -0.44= 896499 [79] 1.72817983 -1.13197006 3.10548018 4.49461712 2.10152842 4.69= 690834 [85] 3.39922575 3.16603618 -1.12129236 3.75663566 1.58317379 4.26= 059766 [91] 0.91838379 1.91024851 4.09803929 2.14609306 0.98833217 2.75= 162381 [97] 1.81045836 0.87533777 0.63199948 0.18344066 -1.54025210 0.23= 425787 [103] 0.80153991 0.94887259 0.06943306 2.39996953 -1.41065690 1.00= 739854 [109] -3.83899461 -0.53752253 -0.28800064 -0.25210009 0.31297603 1.78= 450093 [115] 5.05302283 2.48839069 -1.30079354 -0.62959345 0.62667206 4.95= 014964 [121] 1.95043133 0.14525495 3.01857698 0.35436941 0.78416368 0.22= 548448 [127] 2.04326741 0.06874216 -2.07524148 -0.88005153 2.30160356 -2.36= 412541 [133] 2.19116972 -0.41121250 5.00110689 1.68382117 1.45023533 0.81= 779967 [139] -0.84480430 -1.73482270 2.62198854 -2.61896318 3.42261897 4.26= 309575 [145] 3.26525695 3.17263882 2.65645933 1.71130230 3.44862809 0.20= 268776 [151] 1.15200580 0.44839442 1.36702546 0.11790512 -0.24375402 1.57= 702866 [157] 1.77033570 -2.99595711 2.37607936 3.65182474 2.18867494 3.45= 299200 [163] 0.26978345 4.53104868 1.87604903 -1.65134014 2.07875823 1.88= 976928 [169] 1.20580964 -1.05023794 0.47757510 3.27415777 3.02438409 -0.16= 796632 [175] 2.59291582 1.34009753 1.63429809 -1.09995260 -0.25282263 1.93= 945274 [181] 2.84386817 3.66277324 -0.86760097 0.31237487 2.48537729 0.37= 393541 [187] -1.54643205 5.08228036 -3.37771315 -0.08407991 -2.35993735 1.37= 779282 [193] 1.79250206 -0.18933285 -0.37120536 1.14680133 -0.90535391 -0.76= 086874 [199] -0.37739976 6.00019593
ace
#fitSimGau <- glmssn(Sim_Values ~ X1 + F1, ssn.object =3D sim1.ssn,
data(modelFits) #make sure fitSimGau has the correct path, will vary for each users i= nstallation #predictions depend on distance matrix created earlier with createDis= tMat function #path of this lsn directory was created with createSSN fitSimGau$ssn.object@path <- paste(tempdir(),"/sim1", sep =3D "")
summary(fitSimGau) =
Call: glmssn(formula =3D Sim_Values ~ X1 + F1, ssn.object =3D sim1.ssn, =
CorModels =3D c("Exponential.tailup", "Exponential.taildown"), = addfunccol =3D "addfunccol")=
Residuals: Min 1Q Median 3Q Max =
-3.4017 -1.1714 0.4401 1.1060 4.6293 =
=
Coefficients: Estimate Std. Error t value Pr(>|t|) =
(Intercept) -0.65419 0.45644 -1.433 0.155 =
X1 0.41216 0.06982 5.903 <2e-16 *** F11 0.00000 NA NA NA =
Signif. codes: 0 =E2=80=98***=E2=80=99 0.001 =E2=80=98**=E2=80=99 0.01= =E2=80=98*=E2=80=99 0.05 =E2=80=98.=E2=80=99 0.1 =E2=80=98 =E2=80=99 1
Covariance Parameters: Covariance.Model Parameter Estimate Exponential.tailup parsill 3.22828 Exponential.tailup range 4.24424 Exponential.taildown parsill 0.00140 Exponential.taildown range 9.09635 Nugget parsill 0.08062
Residual standard error: 1.81942 Generalized R-squared: 0.7705965
=
pred1.ssn <- predict(fitSimGau,"preds") Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced Warning in sqrt(vec[n + p + 1] - tlam %% vec[1:n] + t(m) %% vec[(n + = 1):(n + : NaNs produced par(bg =3D "grey60") plot(pred1.ssn, color.palette =3D terrain.colors(10)) Error in quantile.default(cexVals, seq(0, 1, by =3D 0.2)) : =
missing values and NaN's not allowed if 'na.rm' is FALSECalls: plot ... plot.glmssn.predict -> quantile -> quantile.default Execution halted
Package: SubpathwayGMir Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... 2: get_vs_ref(graph) 3: update_vs_ref(graph) 4: V(graphList[[t]]) 5: getInteGraphList(DirectGraphList, relations) 6: eval(expr, envir, enclos) 7: eval(expr, .GlobalEnv) 8: withVisible(eval(expr, .GlobalEnv)) 9: doTryCatch(return(expr), name, parentenv, handler) 10: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 11: tryCatchList(expr, classes, parentenv, handlers) 12: tryCatch(expr, error =3D function(e) { call <- conditionCall(e) = if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatc= h))) call <- sys.call(-4L) dcall <- deparse(call)[1L] = prefix <- paste("Error in", dcall, ": ") LONG <- 75L = msg <- conditionMessage(e) sm <- strsplit(msg, "\n")[[1L]] = w <- 14L + nchar(dcall, type =3D "w") + nchar(sm[1L], type =3D "w") = if (is.na(w)) w <- 14L + nchar(dcall, type =3D "b") + ncha= r(sm[1L], type =3D "b") if (w > LONG) = prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg= <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(= msg[1L])) if (!silent && identical(getOption("show.error.messages"), = TRUE)) { cat(msg, file =3D stderr()) .Internal(print= DeferredWarnings()) } invisible(structure(msg, class =3D "try-error= ", condition =3D e))}) 13: try(withVisible(eval(expr, .GlobalEnv)), silent =3D TRUE) 14: evalFunc(ce, options) 15: tryCatchList(expr, classes, parentenv, handlers) 16: tryCatch(evalFunc(ce, options), finally =3D { cat("\n") sink(= )}) 17: driver$runcode(drobj, chunk, chunkopts) 18: utils::Sweave(...) 19: engine$weave(file, quiet =3D quiet, encoding =3D enc) 20: doTryCatch(return(expr), name, parentenv, handler) 21: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 22: tryCatchList(expr, classes, parentenv, handlers) 23: tryCatch({ engine$weave(file, quiet =3D quiet, encoding =3D enc)= setwd(startdir) find_vignette_product(name, by =3D "weave", engine= =3D engine)}, error =3D function(e) { stop(gettextf("processing vigne= tte '%s' failed with diagnostics:\n%s", file, conditionMessage(e)= ), domain =3D NA, call. =3D FALSE)}) 24: buildVignettes(dir =3D "/home/hornik/tmp/CRAN/SubpathwayGMir.Rcheck= /vign_test/SubpathwayGMir") aborting ... Segmentation fault
Package: SubpathwayGMir Check: running R code from vignettes New result: ERROR Errors in running code in vignettes: when running code in =E2=80=98SubpathwayGMir.Rnw=E2=80=99 ... 9: source(output, echo =3D TRUE) 10: doTryCatch(return(expr), name, parentenv, handler) 11: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 12: tryCatchList(expr, classes, parentenv, handlers) 13: tryCatch({ source(output, echo =3D TRUE)}, error =3D function(e)= { cat("\n When sourcing ", sQuote(output), ":\n", sep =3D "") sto= p(conditionMessage(e), call. =3D FALSE, domain =3D NA)}) 14: tools:::.run_one_vignette("SubpathwayGMir.Rnw", "/home/hornik/tmp/C= RAN/SubpathwayGMir.Rcheck/00_pkg_src/SubpathwayGMir/vignettes", pkgdi= r =3D "/home/hornik/tmp/CRAN/SubpathwayGMir.Rcheck/00_pkg_src/SubpathwayG= Mir") aborting ... Segmentation fault
... incomplete output. Crash?
Package: VineCopula Check: examples New result: ERROR Running examples in =E2=80=98VineCopula-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
ls
=
=
RVM <- RVineStructureSelect(daxreturns[,1:3], c(1:6)) Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Error in RVineMatrix(M, family =3D Type, par =3D Param, par2 =3D Params= 2, names =3D nam) : =
Error in the structure matrix.Calls: RVineStructureSelect -> as.RVM -> RVineMatrix Execution halted
Package: adegenet Check: examples Old result: ERROR Running examples in =E2=80=98adegenet-Ex.R=E2=80=99 failed The error most likely occurred in:
=
=
df <- data.frame(locusA=3Dc("11","11","12","32"),
- locusB=3Dc(NA,"34","55","15"),locusC=3Dc("22","22","21","22"))
obj <- df2genind(df, ploidy=3D2) Error in while (keepCheck) { : missing value where TRUE/FALSE needed Calls: df2genind -> fillWithZero Execution halted New result: ERROR Running examples in =E2=80=98adegenet-Ex.R=E2=80=99 failed The error most likely occurred in: =
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
df <- data.frame(locusA=3Dc("11","11","12","32"),
- locusB=3Dc(NA,"34","55","15"),locusC=3Dc("22","22","21","22"))
obj <- df2genind(df, ploidy=3D2) Error in while (keepCheck) { : missing value where TRUE/FALSE needed Calls: df2genind -> fillWithZero Execution halted
Package: adegenet Check: R code for possible problems Old result: NOTE HWE.test.genind : ftest: no visible global function definition for =E2=80=98HWE.chisq=E2=80=99 HWE.test.genind : ftest: no visible global function definition for =E2=80=98genotype=E2=80=99 alignment2genind: no visible binding for global variable =E2=80=98s2c=E2= =80=99 chooseCN: no visible global function definition for =E2=80=98tri2nb=E2=80= =99 chooseCN: no visible global function definition for =E2=80=98gabrielnei= gh=E2=80=99 chooseCN: no visible global function definition for =E2=80=98graph2nb=E2= =80=99 chooseCN: no visible global function definition for =E2=80=98relativene= igh=E2=80=99 chooseCN: no visible global function definition for =E2=80=98dnearneigh= =E2=80=99 chooseCN: no visible global function definition for =E2=80=98knearneigh= =E2=80=99 chooseCN: no visible global function definition for =E2=80=98knn2nb=E2=80= =99 chooseCN: no visible global function definition for =E2=80=98nb2listw=E2= =80=99 chooseCN: no visible global function definition for =E2=80=98mat2listw=E2= =80=99 fasta2DNAbin: no visible global function definition for =E2=80=98seg.si= tes=E2=80=99 fasta2genlight: no visible global function definition for =E2=80=98mcla= pply=E2=80=99 fstat: no visible global function definition for =E2=80=98varcomp.glob=E2= =80=99 genind2genotype : f2: no visible global function definition for =E2=80=98as.genotype=E2=80=99 genind2genotype: no visible global function definition for =E2=80=98makeGenotypes=E2=80=99 glPca: no visible global function definition for =E2=80=98mclapply=E2=80= =99 global.rtest: no visible global function definition for =E2=80=98orthobasis.listw=E2=80=99 gstat.randtest: no visible global function definition for =E2=80=98g.stats.glob=E2=80=99 gstat.randtest : : no visible global function definition for=
=E2=80=98g.stats.glob=E2=80=99gstat.randtest : : no visible global function definition for=
=E2=80=98samp.within=E2=80=99gstat.randtest : : no visible global function definition for=
=E2=80=98samp.between=E2=80=99local.rtest: no visible global function definition for =E2=80=98orthobasis.listw=E2=80=99 plot.spca: no visible global function definition for =E2=80=98card=E2=80= =99 read.PLINK: no visible global function definition for =E2=80=98mclapply= =E2=80=99 read.snp: no visible global function definition for =E2=80=98mclapply=E2= =80=99 snpposi.plot.DNAbin: no visible global function definition for =E2=80=98seg.sites=E2=80=99 snpposi.test.DNAbin: no visible global function definition for =E2=80=98seg.sites=E2=80=99 spca: no visible global function definition for =E2=80=98mat2listw=E2=80= =99 spca: no visible global function definition for =E2=80=98nb2listw=E2=80= =99 summary.spca: no visible global function definition for =E2=80=98listw2= mat=E2=80=99 summary.spca: no visible binding for global variable =E2=80=98lag.listw= =E2=80=99 New result: NOTE HWE.test.genind : ftest: no visible global function definition for =E2=80=98HWE.chisq=E2=80=99 HWE.test.genind : ftest: no visible global function definition for =E2=80=98genotype=E2=80=99 alignment2genind: no visible binding for global variable =E2=80=98s2c=E2= =80=99 as.igraph.haploGen: possible error in layout.fruchterman.reingold(out, params =3D list(miny =3D ypos, maxy =3D ypos)): unused argument (para= ms =3D list(miny =3D ypos, maxy =3D ypos)) as.igraph.seqTrack: possible error in layout.fruchterman.reingold(out, params =3D list(miny =3D ypos, maxy =3D ypos)): unused argument (para= ms =3D list(miny =3D ypos, maxy =3D ypos)) chooseCN: no visible global function definition for =E2=80=98tri2nb=E2=80= =99 chooseCN: no visible global function definition for =E2=80=98gabrielnei= gh=E2=80=99 chooseCN: no visible global function definition for =E2=80=98graph2nb=E2= =80=99 chooseCN: no visible global function definition for =E2=80=98relativene= igh=E2=80=99 chooseCN: no visible global function definition for =E2=80=98dnearneigh= =E2=80=99 chooseCN: no visible global function definition for =E2=80=98knearneigh= =E2=80=99 chooseCN: no visible global function definition for =E2=80=98knn2nb=E2=80= =99 chooseCN: no visible global function definition for =E2=80=98nb2listw=E2= =80=99 chooseCN: no visible global function definition for =E2=80=98mat2listw=E2= =80=99 fasta2DNAbin: no visible global function definition for =E2=80=98seg.si= tes=E2=80=99 fasta2genlight: no visible global function definition for =E2=80=98mcla= pply=E2=80=99 fstat: no visible global function definition for =E2=80=98varcomp.glob=E2= =80=99 genind2genotype : f2: no visible global function definition for =E2=80=98as.genotype=E2=80=99 genind2genotype: no visible global function definition for =E2=80=98makeGenotypes=E2=80=99 glPca: no visible global function definition for =E2=80=98mclapply=E2=80= =99 global.rtest: no visible global function definition for =E2=80=98orthobasis.listw=E2=80=99 gstat.randtest: no visible global function definition for =E2=80=98g.stats.glob=E2=80=99 gstat.randtest : : no visible global function definition for=
=E2=80=98g.stats.glob=E2=80=99gstat.randtest : : no visible global function definition for=
=E2=80=98samp.within=E2=80=99gstat.randtest : : no visible global function definition for=
=E2=80=98samp.between=E2=80=99local.rtest: no visible global function definition for =E2=80=98orthobasis.listw=E2=80=99 plot.spca: no visible global function definition for =E2=80=98card=E2=80= =99 read.PLINK: no visible global function definition for =E2=80=98mclapply= =E2=80=99 read.snp: no visible global function definition for =E2=80=98mclapply=E2= =80=99 snpposi.plot.DNAbin: no visible global function definition for =E2=80=98seg.sites=E2=80=99 snpposi.test.DNAbin: no visible global function definition for =E2=80=98seg.sites=E2=80=99 spca: no visible global function definition for =E2=80=98mat2listw=E2=80= =99 spca: no visible global function definition for =E2=80=98nb2listw=E2=80= =99 summary.spca: no visible global function definition for =E2=80=98listw2= mat=E2=80=99 summary.spca: no visible binding for global variable =E2=80=98lag.listw= =E2=80=99
Package: arulesViz Check: examples New result: ERROR Running examples in =E2=80=98arulesViz-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
data(Groceries) rules <- apriori(Groceries, parameter=3Dlist(support=3D0.005, confide= nce=3D0.5)) =
Parameter specification: confidence minval smax arem aval originalSupport support minlen maxle= n target 0.5 0.1 1 none FALSE TRUE 0.005 1 1= 0 rules ext FALSE
apriori - find association rules with the apriori algorithm version 4.21 (2004.05.09) (c) 1996-2004 Christian Borgelt set item appearances ...[0 item(s)] done [0.00s]. set transactions ...[169 item(s), 9835 transaction(s)] done [0.01s]. sorting and recoding items ... [120 item(s)] done [0.00s]. creating transaction tree ... done [0.01s]. checking subsets of size 1 2 3 4 done [0.01s]. writing ... [120 rule(s)] done [0.00s]. creating S4 object ... done [0.00s].
rules set of 120 rules =
=
plot(rules)
=
library(colorspace) # for sequential_hcl plot(rules, control=3Dlist(col=3Dsequential_hcl(100))) =
plot(rules, shading=3D"order", control=3Dlist(main =3D "Two-key plot"= , =
- col=3Drainbow(5)))
=
subrules <- subset(rules, lift>2.5) subrules set of 41 rules =
=
plot(subrules, method=3D"matrix", measure=3D"lift") Itemsets in Antecedent (LHS) [1] "{root vegetables,onions}" =
[2] "{onions,whole milk}" =
[3] "{chicken,root vegetables}" =
[4] "{root vegetables,frozen vegetables}" =
[5] "{tropical fruit,curd}" =
[6] "{root vegetables,curd}" =
[7] "{pork,root vegetables}" =
[8] "{root vegetables,margarine}" =
[9] "{butter,whipped/sour cream}" =
[10] "{tropical fruit,butter}" =
[11] "{root vegetables,butter}" =
[12] "{butter,yogurt}" =
[13] "{root vegetables,newspapers}" =
[14] "{whipped/sour cream,domestic eggs}" =
[15] "{root vegetables,domestic eggs}" =
[16] "{root vegetables,fruit/vegetable juice}" =
[17] "{pip fruit,whipped/sour cream}" =
[18] "{citrus fruit,whipped/sour cream}" =
[19] "{tropical fruit,whipped/sour cream}" =
[20] "{root vegetables,whipped/sour cream}" =
[21] "{pip fruit,root vegetables}" =
[22] "{root vegetables,pastry}" =
[23] "{citrus fruit,root vegetables}" =
[24] "{root vegetables,shopping bags}" =
[25] "{tropical fruit,root vegetables}" =
[26] "{root vegetables,yogurt}" =
[27] "{root vegetables,rolls/buns}" =
[28] "{whole milk,yogurt,fruit/vegetable juice}" =
[29] "{root vegetables,whole milk,whipped/sour cream}" [30] "{whole milk,yogurt,whipped/sour cream}" =
[31] "{pip fruit,root vegetables,other vegetables}" =
[32] "{pip fruit,root vegetables,whole milk}" =
[33] "{pip fruit,whole milk,yogurt}" =
[34] "{citrus fruit,root vegetables,whole milk}" =
[35] "{tropical fruit,root vegetables,yogurt}" =
[36] "{tropical fruit,root vegetables,whole milk}" =
[37] "{tropical fruit,whole milk,yogurt}" =
[38] "{root vegetables,whole milk,yogurt}" =
Itemsets in Consequent (RHS) [1] "{other vegetables}" "{yogurt}" "{whole milk}" =
plot(subrules, method=3D"matrix", measure=3D"lift", control=3Dlist(re= order=3DTRUE)) Itemsets in Antecedent (LHS) [1] "{tropical fruit,curd}" =
[2] "{root vegetables,yogurt}" =
[3] "{root vegetables,whipped/sour cream}" =
[4] "{root vegetables,rolls/buns}" =
[5] "{tropical fruit,whole milk,yogurt}" =
[6] "{root vegetables,curd}" =
[7] "{whipped/sour cream,domestic eggs}" =
[8] "{root vegetables,domestic eggs}" =
[9] "{root vegetables,butter}" =
[10] "{whole milk,yogurt,whipped/sour cream}" =
[11] "{pork,root vegetables}" =
[12] "{root vegetables,shopping bags}" =
[13] "{root vegetables,newspapers}" =
[14] "{pip fruit,root vegetables}" =
[15] "{citrus fruit,whipped/sour cream}" =
[16] "{chicken,root vegetables}" =
[17] "{root vegetables,frozen vegetables}" =
[18] "{pip fruit,whole milk,yogurt}" =
[19] "{root vegetables,margarine}" =
[20] "{root vegetables,pastry}" =
[21] "{whole milk,yogurt,fruit/vegetable juice}" =
[22] "{root vegetables,whole milk,yogurt}" =
[23] "{onions,whole milk}" =
[24] "{root vegetables,whole milk,whipped/sour cream}" [25] "{root vegetables,fruit/vegetable juice}" =
[26] "{tropical fruit,butter}" =
[27] "{tropical fruit,whipped/sour cream}" =
[28] "{tropical fruit,root vegetables}" =
[29] "{tropical fruit,root vegetables,whole milk}" =
[30] "{citrus fruit,root vegetables}" =
[31] "{root vegetables,onions}" =
[32] "{pip fruit,root vegetables,whole milk}" =
[33] "{citrus fruit,root vegetables,whole milk}" =
[34] "{pip fruit,whipped/sour cream}" =
[35] "{butter,whipped/sour cream}" =
[36] "{butter,yogurt}" =
[37] "{pip fruit,root vegetables,other vegetables}" =
[38] "{tropical fruit,root vegetables,yogurt}" =
Itemsets in Consequent (RHS) [1] "{other vegetables}" "{yogurt}" "{whole milk}" =
=
plot(subrules, method=3D"matrix3D", measure=3D"lift") Itemsets in Antecedent (LHS) [1] "{root vegetables,onions}" =
[2] "{onions,whole milk}" =
[3] "{chicken,root vegetables}" =
[4] "{root vegetables,frozen vegetables}" =
[5] "{tropical fruit,curd}" =
[6] "{root vegetables,curd}" =
[7] "{pork,root vegetables}" =
[8] "{root vegetables,margarine}" =
[9] "{butter,whipped/sour cream}" =
[10] "{tropical fruit,butter}" =
[11] "{root vegetables,butter}" =
[12] "{butter,yogurt}" =
[13] "{root vegetables,newspapers}" =
[14] "{whipped/sour cream,domestic eggs}" =
[15] "{root vegetables,domestic eggs}" =
[16] "{root vegetables,fruit/vegetable juice}" =
[17] "{pip fruit,whipped/sour cream}" =
[18] "{citrus fruit,whipped/sour cream}" =
[19] "{tropical fruit,whipped/sour cream}" =
[20] "{root vegetables,whipped/sour cream}" =
[21] "{pip fruit,root vegetables}" =
[22] "{root vegetables,pastry}" =
[23] "{citrus fruit,root vegetables}" =
[24] "{root vegetables,shopping bags}" =
[25] "{tropical fruit,root vegetables}" =
[26] "{root vegetables,yogurt}" =
[27] "{root vegetables,rolls/buns}" =
[28] "{whole milk,yogurt,fruit/vegetable juice}" =
[29] "{root vegetables,whole milk,whipped/sour cream}" [30] "{whole milk,yogurt,whipped/sour cream}" =
[31] "{pip fruit,root vegetables,other vegetables}" =
[32] "{pip fruit,root vegetables,whole milk}" =
[33] "{pip fruit,whole milk,yogurt}" =
[34] "{citrus fruit,root vegetables,whole milk}" =
[35] "{tropical fruit,root vegetables,yogurt}" =
[36] "{tropical fruit,root vegetables,whole milk}" =
[37] "{tropical fruit,whole milk,yogurt}" =
[38] "{root vegetables,whole milk,yogurt}" =
Itemsets in Consequent (RHS) [1] "{other vegetables}" "{yogurt}" "{whole milk}" =
plot(subrules, method=3D"matrix3D", measure=3D"lift", control=3Dlist(= reorder=3DTRUE)) Itemsets in Antecedent (LHS) [1] "{tropical fruit,curd}" =
[2] "{root vegetables,yogurt}" =
[3] "{root vegetables,whipped/sour cream}" =
[4] "{root vegetables,rolls/buns}" =
[5] "{tropical fruit,whole milk,yogurt}" =
[6] "{root vegetables,curd}" =
[7] "{whipped/sour cream,domestic eggs}" =
[8] "{root vegetables,domestic eggs}" =
[9] "{root vegetables,butter}" =
[10] "{whole milk,yogurt,whipped/sour cream}" =
[11] "{pork,root vegetables}" =
[12] "{root vegetables,shopping bags}" =
[13] "{root vegetables,newspapers}" =
[14] "{pip fruit,root vegetables}" =
[15] "{citrus fruit,whipped/sour cream}" =
[16] "{chicken,root vegetables}" =
[17] "{root vegetables,frozen vegetables}" =
[18] "{pip fruit,whole milk,yogurt}" =
[19] "{root vegetables,margarine}" =
[20] "{root vegetables,pastry}" =
[21] "{whole milk,yogurt,fruit/vegetable juice}" =
[22] "{root vegetables,whole milk,yogurt}" =
[23] "{onions,whole milk}" =
[24] "{root vegetables,whole milk,whipped/sour cream}" [25] "{root vegetables,fruit/vegetable juice}" =
[26] "{tropical fruit,butter}" =
[27] "{tropical fruit,whipped/sour cream}" =
[28] "{tropical fruit,root vegetables}" =
[29] "{tropical fruit,root vegetables,whole milk}" =
[30] "{citrus fruit,root vegetables}" =
[31] "{root vegetables,onions}" =
[32] "{pip fruit,root vegetables,whole milk}" =
[33] "{citrus fruit,root vegetables,whole milk}" =
[34] "{pip fruit,whipped/sour cream}" =
[35] "{butter,whipped/sour cream}" =
[36] "{butter,yogurt}" =
[37] "{pip fruit,root vegetables,other vegetables}" =
[38] "{tropical fruit,root vegetables,yogurt}" =
Itemsets in Consequent (RHS) [1] "{other vegetables}" "{yogurt}" "{whole milk}" =
=
plot(subrules, method=3D"matrix", measure=3Dc("lift", "confidence")) Itemsets in Antecedent (LHS) [1] "{root vegetables,onions}" =
[2] "{onions,whole milk}" =
[3] "{chicken,root vegetables}" =
[4] "{root vegetables,frozen vegetables}" =
[5] "{tropical fruit,curd}" =
[6] "{root vegetables,curd}" =
[7] "{pork,root vegetables}" =
[8] "{root vegetables,margarine}" =
[9] "{butter,whipped/sour cream}" =
[10] "{tropical fruit,butter}" =
[11] "{root vegetables,butter}" =
[12] "{butter,yogurt}" =
[13] "{root vegetables,newspapers}" =
[14] "{whipped/sour cream,domestic eggs}" =
[15] "{root vegetables,domestic eggs}" =
[16] "{root vegetables,fruit/vegetable juice}" =
[17] "{pip fruit,whipped/sour cream}" =
[18] "{citrus fruit,whipped/sour cream}" =
[19] "{tropical fruit,whipped/sour cream}" =
[20] "{root vegetables,whipped/sour cream}" =
[21] "{pip fruit,root vegetables}" =
[22] "{root vegetables,pastry}" =
[23] "{citrus fruit,root vegetables}" =
[24] "{root vegetables,shopping bags}" =
[25] "{tropical fruit,root vegetables}" =
[26] "{root vegetables,yogurt}" =
[27] "{root vegetables,rolls/buns}" =
[28] "{whole milk,yogurt,fruit/vegetable juice}" =
[29] "{root vegetables,whole milk,whipped/sour cream}" [30] "{whole milk,yogurt,whipped/sour cream}" =
[31] "{pip fruit,root vegetables,other vegetables}" =
[32] "{pip fruit,root vegetables,whole milk}" =
[33] "{pip fruit,whole milk,yogurt}" =
[34] "{citrus fruit,root vegetables,whole milk}" =
[35] "{tropical fruit,root vegetables,yogurt}" =
[36] "{tropical fruit,root vegetables,whole milk}" =
[37] "{tropical fruit,whole milk,yogurt}" =
[38] "{root vegetables,whole milk,yogurt}" =
Itemsets in Consequent (RHS) [1] "{other vegetables}" "{yogurt}" "{whole milk}" =
plot(subrules, method=3D"matrix", measure=3Dc("lift", "confidence"), =
- control=3Dlist(reorder=3DTRUE)) Itemsets in Antecedent (LHS) [1] "{tropical fruit,curd}" =
[2] "{root vegetables,whipped/sour cream}" =
[3] "{root vegetables,yogurt}" =
[4] "{root vegetables,rolls/buns}" =
[5] "{tropical fruit,whole milk,yogurt}" =
[6] "{root vegetables,curd}" =
[7] "{whipped/sour cream,domestic eggs}" =
[8] "{root vegetables,domestic eggs}" =
[9] "{root vegetables,butter}" =
[10] "{whole milk,yogurt,whipped/sour cream}" =
[11] "{pork,root vegetables}" =
[12] "{root vegetables,shopping bags}" =
[13] "{root vegetables,newspapers}" =
[14] "{pip fruit,root vegetables}" =
[15] "{citrus fruit,whipped/sour cream}" =
[16] "{chicken,root vegetables}" =
[17] "{root vegetables,frozen vegetables}" =
[18] "{pip fruit,whole milk,yogurt}" =
[19] "{root vegetables,margarine}" =
[20] "{root vegetables,pastry}" =
[21] "{whole milk,yogurt,fruit/vegetable juice}" =
[22] "{root vegetables,whole milk,yogurt}" =
[23] "{onions,whole milk}" =
[24] "{root vegetables,whole milk,whipped/sour cream}" [25] "{root vegetables,fruit/vegetable juice}" =
[26] "{tropical fruit,butter}" =
[27] "{tropical fruit,whipped/sour cream}" =
[28] "{tropical fruit,root vegetables}" =
[29] "{tropical fruit,root vegetables,whole milk}" =
[30] "{citrus fruit,root vegetables}" =
[31] "{root vegetables,onions}" =
[32] "{pip fruit,root vegetables,whole milk}" =
[33] "{citrus fruit,root vegetables,whole milk}" =
[34] "{pip fruit,whipped/sour cream}" =
[35] "{butter,whipped/sour cream}" =
[36] "{butter,yogurt}" =
[37] "{pip fruit,root vegetables,other vegetables}" =
[38] "{tropical fruit,root vegetables,yogurt}" =
Itemsets in Consequent (RHS) [1] "{other vegetables}" "{yogurt}" "{whole milk}" =
=
ve=3DTRUE, =
=
plot(rules, method=3D"grouped")
=
subrules2 <- sample(rules, 10) plot(subrules2, method=3D"graph") Error in control$layout(g, params =3D control$layoutParams) : =
unused argument (params =3D control$layoutParams)Calls: plot ... plot -> plot.igraph -> i.parse.plot.params -> <Anonymou= s> Execution halted
Package: arulesViz Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... Loading required package: arules Loading required package: Matrix
%in%, write=
Loading required package: grid Warning: replacing previous import by =E2=80=98igraph::union=E2=80=99 w= hen loading =E2=80=98arulesViz=E2=80=99 Warning: replacing previous import by =E2=80=98seriation::permute=E2=80= =99 when loading =E2=80=98arulesViz=E2=80=99
abbreviate=
=
Error: processing vignette =E2=80=98arulesViz.Rnw=E2=80=99 failed with = diagnostics: chunk 23 (label =3D graph1) =
Error in control$layout(g, params =3D control$layoutParams) : =
unused argument (params =3D control$layoutParams)Execution halted
Package: arulesViz Check: running R code from vignettes New result: ERROR Errors in running code in vignettes: when running code in =E2=80=98arulesViz.Rnw=E2=80=99 ...
plot(rules, method =3D "grouped", control =3D list(k =3D 50)) =
subrules2 <- head(sort(rules, by =3D "lift"), 10) =
plot(subrules2, method =3D "graph", control =3D list(type =3D "items"= )) =
When sourcing =E2=80=98arulesViz.R=E2=80=99:Error: unused argument (params =3D control$layoutParams) Execution halted
Package: arulesViz Check: whether package can be installed New result: WARNING Found the following significant warnings: Warning: replacing previous import by =E2=80=98igraph::union=E2=80=99= when loading =E2=80=98arulesViz=E2=80=99 Warning: replacing previous import by =E2=80=98seriation::permute=E2=80= =99 when loading =E2=80=98arulesViz=E2=80=99 See =E2=80=98/home/hornik/tmp/CRAN/arulesViz.Rcheck/00install.out=E2=80= =99 for details.
Package: causaleffect Check: whether package can be installed New result: WARNING Found the following significant warnings: Warning: replacing previous import by =E2=80=98igraph::pa=E2=80=99 wh= en loading =E2=80=98causaleffect=E2=80=99 See =E2=80=98/home/hornik/tmp/CRAN/causaleffect.Rcheck/00install.out=E2= =80=99 for details.
Package: cccd Check: examples New result: ERROR Running examples in =E2=80=98cccd-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
er.rw
=
=
set.seed(456330) z <- matrix(runif(1000),ncol=3D2) ind <- which(z[,1]<.5 & z[,2]<.5) x <- z[ind,] y <- z[-ind,] g <- cccd(x,y) C <- cccd.classifier(x,y) Error in graph(n =3D vc, edges, directed =3D (mode =3D=3D "directed")) = : =
'edges' must be numeric of characterCalls: cccd.classifier ... dominate.greedy -> graph.adjacency -> graph.= adjacency.sparse -> graph Execution halted
Package: dnet Check: examples New result: ERROR Running examples in =E2=80=98dnet-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
graph
=
=
ution
module <- dNetFind(subg, scores) Error in eval(expr, envir, enclos) : object 'X' not found Calls: dNetFind ... FUN -> [ -> [.igraph.vs -> lazy_eval -> eval -> eva= l Execution halted
Package: fanovaGraph Check: tests New result: ERROR Running the tests in =E2=80=98tests/run-all.R=E2=80=99 failed. Last 13 lines of output: F =3D -9.97537 final value -9.975373 =
converged threshold RMSE [1,] 0.0 0.3281777 [2,] 0.4 0.2187619 [3,] 1.0 0.9907953 testthat results =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D==3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D OK: 31 SKIPPED: 0 FAILED: 1 1. Failure (at test_fullexample.R#78): the full example works as befo= re =
= Error: testthat unit tests failed Execution haltedPackage: gRapfa Check: examples New result: ERROR Running examples in =E2=80=98gRapfa-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
library(gRapfa) data(Wheeze) samp <- sample(1:537, 250) G <- select.IC(Wheeze[samp,]) G.fit <- fit.APFA(G, Wheeze[-samp,]) Warning in Ops.factor(a$from, 1) : =E2=80=98-=E2=80=99 not meaningful f= or factors Warning in Ops.factor(from, 1) : =E2=80=98-=E2=80=99 not meaningful for= factors Warning in Ops.factor(from, 1) : =E2=80=98-=E2=80=99 not meaningful for= factors Warning in Ops.factor(from, 1) : =E2=80=98-=E2=80=99 not meaningful for= factors Error in eattrs[[name]][index] <- value : replacement has length zero Calls: fit.APFA -> E<- -> i_set_edge_attr Execution halted
Package: gemtc Check: examples New result: ERROR Running examples in =E2=80=98gemtc-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
file <- system.file("extdata/luades-smoking.gemtc", package=3D"gemtc"= ) network <- read.mtc.network(file) =
model <- mtc.model(network, type=3D"consistency") Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Warning: 'get.edge' is deperecated, please use 'ends' instead. Error in eval(expr, envir, enclos) : object 'newX' not found Calls: mtc.model ... FUN -> [ -> [.igraph.vs -> lazy_eval -> eval -> ev= al Execution halted
Package: gemtc Check: tests New result: ERROR Running the tests in =E2=80=98tests/test.R=E2=80=99 failed. Last 13 lines of output: 9. Error: tree.relative.effect handles a simple tree =
1. Error: tree.relative.effect handles a more complex tree = 2. Error: tree.relative.effect handles two-treatment case = 3. Error: relative.effect can be applied recursively = 4. Error: rank.probability returns the right results = 5. Error: rank.probability can be applied to a subset of parameters = 6. Error: spanning.tree.mtc.result handles two-treatment case = 7. Error: relative.effect is robust to missing sd.d = 8. Error: relative.effect is robust to leading columns = 9. ... = Error: testthat unit tests failed Execution haltedPackage: intergraph Check: examples New result: ERROR Running examples in =E2=80=98intergraph-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
d1 <- asDF(exNetwork) str(d1) List of 2 $ edges :'data.frame': 11 obs. of 4 variables: ..$ V1 : int [1:11] 2 3 4 5 6 8 10 11 14 12 ... ..$ V2 : int [1:11] 1 1 1 1 7 9 11 12 12 13 ... ..$ label: chr [1:11] "ba" "ca" "da" "ea" ... ..$ na : logi [1:11] FALSE FALSE FALSE FALSE FALSE FALSE ... $ vertexes:'data.frame': 15 obs. of 4 variables: ..$ intergraph_id: int [1:15] 1 2 3 4 5 6 7 8 9 10 ... ..$ label : chr [1:15] "a" "b" "c" "d" ... ..$ na : logi [1:15] FALSE FALSE FALSE FALSE FALSE FALSE ..= =2E ..$ vertex.names : chr [1:15] "a" "b" "c" "d" ...
d2 <- asDF(exIgraph) Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly... =
Traceback: 1: base::.Call("R_igraph_mybracket", graph, 10L, PACKAGE =3D "igraph")=
2: get_vs_ref(graph) 3: update_es_ref(graph) 4: E(graph) 5: inherits(e, "igraph.es") 6: as.igraph.es(graph, index) 7: igraph::get.edge.attribute(x, a) 8: FUN(X[[i]], ...) 9: lapply(nams, function(a) igraph::get.edge.attribute(x, a)) 10: dumpAttr.igraph(object, "edge") 11: dumpAttr(object, "edge") 12: asDF.igraph(exIgraph) 13: asDF(exIgraph) aborting ... Segmentation fault
Package: intergraph Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... 15: asNetwork(exIgraph) 16: eval(expr, envir, enclos) 17: eval(expr, envir, enclos) 18: withVisible(eval(expr, envir, enclos)) 19: withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning= =3D wHandler, error =3D eHandler, message =3D mHandler) 20: handle(ev <- withCallingHandlers(withVisible(eval(expr, envir, = enclos)), warning =3D wHandler, error =3D eHandler, message =3D mHandler)= ) 21: evaluate_call(expr, parsed$src[[i]], envir =3D envir, enclos =3D en= clos, debug =3D debug, last =3D i =3D=3D length(out), use_try =3D sto= p_on_error !=3D 2L, keep_warning =3D keep_warning, keep_message =3D= keep_message, output_handler =3D output_handler) 22: evaluate::evaluate(code, envir =3D env, new_device =3D FALSE, keep_= warning =3D !isFALSE(options$warning), keep_message =3D !isFALSE(opti= ons$message), stop_on_error =3D if (options$error && options$incl= ude) 0L else 2L, output_handler =3D knit_handlers(options$render, = options)) 23: in_dir(opts_knit$get("root.dir") %n% input_dir(), evaluate::evaluat= e(code, envir =3D env, new_device =3D FALSE, keep_warning =3D !isFALS= E(options$warning), keep_message =3D !isFALSE(options$message), stop_= on_error =3D if (options$error && options$include) 0L else 2L, ou= tput_handler =3D knit_handlers(options$render, options))) 24: block_exec(params) 25: call_block(x) 26: process_group.block(group) 27: process_group(group) 28: withCallingHandlers(if (tangle) process_tangle(group) else process_= group(group), error =3D function(e) { setwd(wd) cat(res= , sep =3D "\n", file =3D output %n% "") message("Quitting from lin= es ", paste(current_lines(i), collapse =3D "-"), " (", knit_c= oncord$get("infile"), ") ") }) 29: process_file(text, output) 30: knit(input, text =3D text, envir =3D envir, encoding =3D encoding, = quiet =3D quiet) 31: (if (grepl("\.[Rr]md$", file)) knit2html else if (grepl("\.[Rr]rs= t$", file)) knit2pdf else knit)(file, encoding =3D encoding, quiet =3D= quiet, envir =3D globalenv()) 32: engine$weave(file, quiet =3D quiet, encoding =3D enc) 33: doTryCatch(return(expr), name, parentenv, handler) 34: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 35: tryCatchList(expr, classes, parentenv, handlers) 36: tryCatch({ engine$weave(file, quiet =3D quiet, encoding =3D enc)= setwd(startdir) find_vignette_product(name, by =3D "weave", engine= =3D engine)}, error =3D function(e) { stop(gettextf("processing vigne= tte '%s' failed with diagnostics:\n%s", file, conditionMessage(e)= ), domain =3D NA, call. =3D FALSE)}) 37: buildVignettes(dir =3D "/home/hornik/tmp/CRAN/intergraph.Rcheck/vig= n_test/intergraph") aborting ... Segmentation fault
Package: intergraph Check: tests New result: ERROR Running the tests in =E2=80=98tests/testall.R=E2=80=99 failed. Last 13 lines of output: 24: test_code(desc, substitute(code), env =3D parent.frame()) 25: test_that("Vertex names are properly set via 'vnames' argument fo= r undirected network", { l <- asDF(exIgraph2) g <- asIg= raph(l$edges, vertices =3D l$vertexes, directed =3D FALSE) expect_= identical(g, exIgraph2) }) 26: eval(expr, envir, enclos) 27: eval(exprs, envir) 28: sys.source2(fname, new.env(parent =3D env)) 29: FUN(X[[i]], ...) 30: lapply(paths, test_file, env =3D env, reporter =3D current_report= er, start_end_reporter =3D FALSE) 31: test_dir(test_path, reporter =3D reporter, env =3D env, filter =3D= filter, ...) 32: with_top_env(env, { test_dir(test_path, reporter =3D reporter,= env =3D env, filter =3D filter, ...)}) 33: run_tests(package, test_path, filter, reporter, ...) 34: test_package("intergraph") aborting ... Segmentation fault
Package: modMax Check: examples New result: ERROR Running examples in =E2=80=98modMax-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
ture
=
=
=
#to ensure that the graph is connected vertices <- which(clusters(randomgraph)$membership=3D=3D1) =
adj <- get.adjacency(graph, attr=3D"weight") result <- extremalOptimization(adj) Error in A[i, neighbors[j]] : =
invalid or not-yet-implemented 'Matrix' subsettingCalls: extremalOptimization -> callExtremalOptimization -> calculateQ -=
[ -> [ Execution halted
Package: modMax Check: whether package can be installed New result: WARNING Found the following significant warnings: Warning: replacing previous import by =E2=80=98gtools::permute=E2=80=99= when loading =E2=80=98modMax=E2=80=99 See =E2=80=98/home/hornik/tmp/CRAN/modMax.Rcheck/00install.out=E2=80=99= for details.
Package: nat Check: Rd cross-references New result: WARNING Missing link or links in documentation object 'ngraph.Rd': =E2=80=98[igraph]{attributes}=E2=80=99
See section 'Cross-references' in the 'Writing R Extensions' manual.
Package: nat Check: tests New result: ERROR Running the tests in =E2=80=98tests/test-all.R=E2=80=99 failed. Last 13 lines of output: 4: graph(NULL, n =3D 1) at test-seglist.R:50 5: stop("'edges' must be numeric of character") =
testthat results =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D==3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D OK: 627 SKIPPED: 0 FAILED: 5 1. Failure (at test-neuroml-io.R#36): parse neuroml files =
2. Failure (at test-ngraph.R#63): equivalence of seglist and swc meth=ods for as.ngraph.neuron =
3. Failure (at test-ngraph.R#64): equivalence of seglist and swc meth=ods for as.ngraph.neuron =
4. Failure (at test-ngraph.R#65): equivalence of seglist and swc meth=ods for as.ngraph.neuron =
5. Error: convert graph to seglist = = Error: testthat unit tests failed Execution haltedPackage: nat Check: whether package can be installed New result: WARNING Found the following significant warnings: Warning: replacing previous import by =E2=80=98nabor::knn=E2=80=99 wh= en loading =E2=80=98nat=E2=80=99 See =E2=80=98/home/hornik/tmp/CRAN/nat.Rcheck/00install.out=E2=80=99 fo= r details.
Package: netassoc Check: examples New result: ERROR Running examples in =E2=80=98netassoc-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
n <- makenetwork(m_obs, m_nul, numnulls=3D50, plot=3DTRUE) Generating null replicates.............................................= =2E..........done. Calculating co-occurrence scores...1 2 0.022 obs. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. =
1 3 0.044 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
1 4 0.067 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
1 5 0.089 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
1 6 0.111 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
1 7 0.133 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
1 8 0.156 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
1 9 0.178 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
1 10 0.200 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
2 3 0.222 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
2 4 0.244 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
2 5 0.267 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
2 6 0.289 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
2 7 0.311 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
2 8 0.333 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
2 9 0.356 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
2 10 0.378 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
3 4 0.400 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
3 5 0.422 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
3 6 0.444 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
3 7 0.467 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
3 8 0.489 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
3 9 0.511 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
3 10 0.533 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
4 5 0.556 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
4 6 0.578 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
4 7 0.600 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
4 8 0.622 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
4 9 0.644 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
4 10 0.667 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
5 6 0.689 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
5 7 0.711 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
5 8 0.733 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
5 9 0.756 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
5 10 0.778 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
6 7 0.800 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
6 8 0.822 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
6 9 0.844 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, me= thod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
6 10 0.867 obs. .. .. .Warning in cor(x =3D veci_nul, y =3D vecj_nul, m= ethod =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .Warning in cor(x =3D veci_nul, y =3D v= ecj_nul, method =3D whichmethod) : the standard deviation is zero . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. .. .. .. .. .. =
7 8 0.889 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
7 9 0.911 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
7 10 0.933 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
8 9 0.956 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..= .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. =
8 10 0.978 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
9 10 1.000 obs. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .= =2E .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. = =2E. .. .. .. .. .. .. .. =
...done. Calculating standardized effect sizes......done. Applying kappa threshold......done. Building network......done. Error in .Call("R_igraph_layout_kamada_kawai", graph, coords, maxiter, = : =
At structural_properties.c:5235 : cannot run Bellman-Ford algorithm, =Negative loop detected while calculating shortest paths Calls: makenetwork ... layout.auto -> layout_with_kk -> .Call -> <Anony= mous> Execution halted
Package: netgsa Check: examples New result: ERROR Running examples in =E2=80=98netgsa-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
##Visualize the networks par(mar =3D c(0.5, 0.5, 3, 0.5)) plot(netgsaex$g.alt, vertex.size =3D 5, vertex.label =3D NA, main=3D"= Network - alt") Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly... Error in assign("me", graph, envir =3D env) : invalid 'envir' argument Calls: plot ... as.igraph.es -> inherits -> E -> update_es_ref -> assig= n Execution halted
Package: optrees Check: examples New result: ERROR Running examples in =E2=80=98optrees-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
nodes <- 1:5 arcs <- matrix(c(1,2,2, 1,3,2, 1,4,3, 2,5,5, 3,2,4, 3,5,3, 4,3,1, 4,5= ,0),
ncol =3D 3, byrow =3D TRUE)getShortestPathTree(nodes, arcs, algorithm =3D "Dijkstra", directed=3D= FALSE) =
Shortest path tree =
Algorithm: Dijkstra =
Stages: 4 | Time: 0.001 =
ept1 ept2 weight = 1 2 2 1 3 2 1 4 3 4 5 0
Total =3D 7 ==
Distances from source: =
source node distance = 1 2 2 1 3 2 1 4 3 1 5 3
=
Error in if (vr[1] =3D=3D vr[2]) { : missing value where TRUE/FALSE nee= ded Calls: getShortestPathTree ... repGraph -> plot.igraph -> norm_coords -=
.layout.norm.col Execution halted
Package: outbreaker Check: examples New result: ERROR Running examples in =E2=80=98outbreaker-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
##D ## COMMAND LINES TO GENERATE SIMILAR DATA ## ##D w <- c(0, 0.5, 1, 0.75) ##D ## note: this works only if outbreak has at least 30 case ##D dat <- simOutbreak(R0 =3D 2, infec.curve =3D w, n.hosts =3D 100)[= 1:30] ##D collecDates <- dat$onset + sample(0:3, size=3D30, replace=3DTRUE,= prob=3Dw)
=
matplot(dat$dynam, type=3D"o", pch=3D20, lty=3D1,
- main=3D"Outbreak dynamics", xlim=3Dc(0,28))
plot(dat, annot=3D"dist", main=3D"Data - transmission tree") Error in layout.fruchterman.reingold(out, params =3D list(minx =3D V(ou= t)$date, : =
unused argument (params =3D list(minx =3D V(out)$date, maxx =3D V(out=)$date)) Calls: plot ... as.igraph.simOutbreak -> layout.fruchterman.reingold Execution halted
Package: outbreaker Check: R code for possible problems New result: NOTE as.igraph.simOutbreak: possible error in layout.fruchterman.reingold(out, params =3D list(minx =3D V(out)$date= , maxx =3D V(out)$date)): unused argument (params =3D list(minx =3D V(out)$date, maxx =3D V(out)$date)) as.igraph.tTree: possible error in layout.fruchterman.reingold(out, params =3D list(minx =3D x$inf.dates, maxx =3D x$inf.dates)): unused argument (params =3D list(minx =3D x$inf.dates, maxx =3D x$inf.dates)= ) transGraph: possible error in layout.fruchterman.reingold(out, params =3D=
list(minx =3D V(out)$onset, maxx =3D V(out)$onset), rescale =3D FALSE=): unused arguments (params =3D list(minx =3D V(out)$onset, maxx =3D V(out)$onset), rescale =3D FALSE)
Package: pcalg Check: examples New result: ERROR Running examples in =E2=80=98pcalg-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
p <- 6 V<-as.character(1:p) edL <- vector("list",length=3D6) names(edL)<-V edL[[1]] <- list(edges=3Dc(3,4),weights=3Dc(1.1,0.3)) edL[[2]] <- list(edges=3Dc(6),weights=3Dc(0.4)) edL[[3]] <- list(edges=3Dc(2,4,6),weights=3Dc(0.6,0.8,0.9)) edL[[4]] <- list(edges=3Dc(2),weights=3Dc(0.5)) edL[[5]] <- list(edges=3Dc(1,4),weights=3Dc(0.2,0.7)) myDAG <- new("graphNEL",nodes=3DV,edgeL=3DedL,edgemode=3D"directed") =
set.seed(123) if (require(mvtnorm)) {
- n <- 1000
- dat <- rmvnorm(n,mean=3Drep(0,p),sigma=3DcovTrue)
- } Loading required package: mvtnorm
=
if (require(Rgraphviz)) {
- par(mfrow =3D c(1,2))
- plot(myDAG, main =3D "True DAG")
- plot(pc.fit, main =3D "Estimated CPDAG")
- } Loading required package: Rgraphviz Loading required package: graph Loading required package: grid
=
jointIda(x.pos=3Dc(1,2),y.pos=3D6,covTrue,graphEst=3DmyCPDAG,techniqu= e=3D"RRC") Error in simple_vs_index(x, ii, na_ok) : Unknown vertex selected Calls: jointIda ... extract.parent.sets -> [ -> [.igraph.vs -> simple_v= s_index Execution halted
Package: pcalg Check: tests New result: ERROR Running the tests in =E2=80=98tests/test_jointIda.R=E2=80=99 failed. Last 13 lines of output: Loading required package: mvtnorm > =
> ## estimate CPDAG -- see help(pc) > suffStat <- list(C =3D cor(dat), n =3D n) > pc.fit <- pc(suffStat, indepTest =3D gaussCItest, p =3D p, alpha =3D=0.01 ,u2pd=3D"relaxed") > =
> Rnd <- 7 > ## Suppose that we know the true CPDAG and covariance matrix > mTrue <- matrix(c(0.99, 0.4, 0.99, 0.4, 0, 0.4), 2,3) > m1 <- round(jointIda(x.pos=3Dc(1,2),y.pos=3D6,covTrue,graphEst=3Dmy=CPDAG,technique=3D"RRC"), Rnd) Error in simple_vs_index(x, ii, na_ok) : Unknown vertex selected Calls: jointIda ... extract.parent.sets -> [ -> [.igraph.vs -> simple= _vs_index Execution halted
Package: popgraph Check: examples New result: ERROR Running examples in =E2=80=98popgraph-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
data(lopho) require(ggplot2) require(igraph) layout <- layout.fruchterman.reingold( lopho ) Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly... Error in assign("me", graph, envir =3D env) : invalid 'envir' argument Calls: layout.fruchterman.reingold -> E -> update_es_ref -> assign Execution halted
Package: poplite Check: examples New result: ERROR Running examples in =E2=80=98poplite-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=2E
=
=
if (require(Lahman))
- {
baseball.teams <- makeSchemaFromData(TeamsFranchises, name=3D"t=eam_franch")
baseball.teams <- append(baseball.teams, makeSchemaFromData(Tea=ms, name=3D"teams"))
=relationship(baseball.teams, from=3D"team_franch", to=3D"teams"=) <- franchID ~ franchID
=baseball.db <- Database(baseball.teams, tempfile())=populate(baseball.db, teams=3DTeams, team_franch=3DTeamsFranchi=ses)
=select(baseball.db, .tables=3D"teams")=select(baseball.db, .tables=3Dc("teams", "team_franch"))=select(baseball.db, yearID:WCWin, franchName)=filter(baseball.db, active =3D=3D "Y")=select(filter(baseball.db, active =3D=3D "Y" & W > 50 & teamID ==3D=3D "CAL"), active, W, teamID)
- } Loading required package: Lahman Starting team_franch Starting teams Error in eval(expr, envir, enclos) : object 'X' not found Calls: select ... FUN -> [ -> [.igraph.vs -> lazy_eval -> eval -> eval Execution halted
Package: poplite Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... The following objects are masked from =E2=80=98package:base=E2=80=99:
intersect, setdiff, setequal, union=
=
select=
filter=
Error in makeSchemaFromData(dna, "dna") : =
ERROR: The names of the supplied data.frame need to be modified for t=Error: processing vignette =E2=80=98poplite.Rnw=E2=80=99 failed with di= agnostics: chunk 9 =
Error in eval(expr, envir, enclos) : object =E2=80=98X=E2=80=99 not fou= nd Execution halted
Package: poplite Check: running R code from vignettes New result: ERROR Errors in running code in vignettes: when running code in =E2=80=98poplite.Rnw=E2=80=99 ... 9 10 1 dna_10_1 10 15 1 dna_15_1 .. ... ... ...
select(sample.tracking.db, .tables =3D c("clinical", =
"dna"))=
When sourcing =E2=80=98poplite.R=E2=80=99:Error: object =E2=80=98X=E2=80=99 not found Execution halted
Package: poplite Check: tests New result: ERROR Running the tests in =E2=80=98tests/testthat.R=E2=80=99 failed. Last 13 lines of output: 16: lazy_eval(args[[idx]], data =3D c(attrs, nei =3D nei, innei =3D i= nnei, outnei =3D outnei, =
adj =3D adj, inc =3D inc, from =3D from, to =3D to)) 17: eval(x$expr, data, x$env) 18: eval(expr, envir, enclos) = testthat results =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D==3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D OK: 129 SKIPPED: 0 FAILED: 3 1. Error: Querying with Database objects =
2. Error: sample tracking example but with direct keys between dna an=d samples =
3. Error: oligoMask queries that break poplite = = Error: testthat unit tests failed Execution haltedPackage: ppiPre Check: examples New result: ERROR Running examples in =E2=80=98ppiPre-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
edges <- data.frame(node1=3Dc("1132", "1133", "1134", "1134", "1145= ", "1147", "1147", "1147"),
node2=3Dc("1134", "1134", "1145", "1147", "1147=", "1148", "1149", "1150"))
graph<-igraph::graph.data.frame(edges,directed=3DFALSE) AASim("1134","1147",graph) Error in
[<-.igraph.vs(*tmp*, 1, value =3D 9) : invalid indexing Calls: AASim -> [<- -> [<-.igraph.vs Execution haltedPackage: qdap Check: Rd cross-references New result: WARNING Missing link or links in documentation object 'plot.cm_distance.Rd': =E2=80=98[igraph]{layout}=E2=80=99
Missing link or links in documentation object 'word_associate.Rd': =E2=80=98[igraph]{layout}=E2=80=99
Missing link or links in documentation object 'word_network_plot.Rd': =E2=80=98[igraph]{igraph.vertex.shapes}=E2=80=99 =E2=80=98[igraph]{la= yout}=E2=80=99
See section 'Cross-references' in the 'Writing R Extensions' manual.
Package: secrlinear Check: examples New result: ERROR Running examples in =E2=80=98secrlinear-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
=
summary(arvicola) Object class capthist =
Detector type multi =
Detector number 88 =
Average spacing 19.80165 m =
x-range 163.85 835.61 m =
y-range 457.67 684.59 m =
Counts by occasion =
1 2 3 4 5 6 Totaln 16 11 18 12 16 11 84 u 16 2 6 1 1 0 26 f 7 3 4 5 3 4 26 M(t+1) 16 18 24 25 26 26 26 losses 0 0 0 0 0 0 0 detections 16 11 18 12 16 11 84 detectors visited 16 11 18 12 16 11 84 detectors used 88 88 88 88 88 88 528
userd <- networkdistance (traps(arvicola), glymemask, glymemask) Warning in warn_version(graph) : This graph was created by an old(er) igraph version. Call upgrade_graph() on it to use with the current igraph version For now we convert it on the fly... =
Traceback: 1: base::.Call("R_igraph_mybracket", graph, 10L, PACKAGE =3D "igraph")=
2: get_vs_ref(graph) 3: update_vs_ref(graph) 4: V(gr) 5: cbind(V(gr)$x, V(gr)$y) 6: networkdistance(traps(arvicola), glymemask, glymemask) aborting ... Segmentation fault
Package: secrlinear Check: re-building of vignette outputs New result: NOTE Error in re-building vignettes: ... Warning in in_dir(opts_knit$get("root.dir") %n% input_dir(), evaluate::= evaluate(code, : You changed the working directory to /home/hornik/tmp/CRAN/secrlinear= =2ERcheck/secrlinear/extdata (probably via setwd()). It will be restored = to /home/hornik/tmp/CRAN/secrlinear.Rcheck/vign_test/secrlinear/vignettes= =2E See the Note section in ?knitr::knit Quitting from lines 72-74 (secrlinear-vignette.Rmd) =
Error: processing vignette =E2=80=98secrlinear-vignette.Rmd=E2=80=99 fa= iled with diagnostics: non-numeric argument to binary operator Execution halted
Package: timeordered Check: examples New result: ERROR Running examples in =E2=80=98timeordered-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
ertex
=
=
data(ants) allindivs <- c(union(ants$VertexFrom, ants$VertexTo), "NULL1", "NULL2= ") g <- generatetonetwork(ants, allindivs) stp <- shortesttimepath(g, "WBGG", 927, "Q") Warning in .Call("R_igraph_get_shortest_paths", graph, as.igraph.vs(gra= ph, : At structural_properties.c:4517 :Couldn't reach some vertices Error in eval(expr, envir, enclos) : object 'X' not found Calls: shortesttimepath ... tail -> [ -> [.igraph.vs -> lazy_eval -> ev= al -> eval Execution halted
Package: treemap Check: examples New result: ERROR Running examples in =E2=80=98treemap-Ex.R=E2=80=99 failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos =3D "CheckExEnv")
=
=
data(business) treegraph(business, index=3Dc("NACE1", "NACE2", "NACE3", "NACE4"), sh= ow.labels=3DFALSE) treegraph(business[business$NACE1=3D=3D"F - Construction",],
index=3Dc("NACE2", "NACE3", "NACE4"), show.labels=3DTRUE, truncat=e.labels=3Dc(2,4,6))
treegraph(business[business$NACE1=3D=3D"F - Construction",],
index=3Dc("NACE2", "NACE3", "NACE4"), show.labels=3DTRUE, truncat=e.labels=3Dc(2,4,6),
vertex.layout=3Digraph::layout.fruchterman.reingold)Error in (function (graph, coords =3D NULL, dim =3D 2, niter =3D 500, s= tart.temp =3D sqrt(vcount(graph)), : =
unused arguments (circular =3D TRUE, root =3D 1)Calls: treegraph -> do.call -> Execution halted